Source code for AISTATS 2019 paper: Lovász Convolutional Networks.

• Compatible with TensorFlow 1.x and Python 3.x.
• Dependencies can be installed using requirements.txt.

• The current code allows evaluation on synthetic datasets which can be downloaded from here.

• Run setup.sh for setting up the environment and extracting the datasets and pre-trained models.
• lcn.py contains TensorFlow (1.x) based implementation of LCN (proposed method).
• Execute evaluate.sh for evaluating pre-trained LCN model on all four datasets.

• Execute setup.sh for setting up the environment and extracting datasets.

• For training LCN run:

  python lcn.py -data citeseer -name new_run -kernel <lovasz/kls/none>

Please cite us if you use this code.

@InProceedings{yadav19a,
  title = 	 {Lovasz Convolutional Networks},
  author = 	 {Yadav, Prateek and Nimishakavi, Madhav and Yadati, Naganand and Vashishth, Shikhar and Rajkumar, Arun and Talukdar, Partha},
  booktitle = 	 {Proceedings of Machine Learning Research},
  pages = 	 {1978--1987},
  year = 	 {2019},
  editor = 	 {Chaudhuri, Kamalika and Sugiyama, Masashi},
  volume = 	 {89},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {},
  month = 	 {16--18 Apr},
  publisher = 	 {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v89/yadav19a/yadav19a.pdf},
  url = 	 {http://proceedings.mlr.press/v89/yadav19a.html}
}

For any clarification, comments, or suggestions please create an issue or contact [email protected].